Concept

Constraint satisfaction problem

Related publications (352)

Learning Generalized Nash Equilibria in a Class of Convex Games

We consider multiagent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we propose a novel dis ...

2019

Definition Of A Transparent Constraint-Based Modeling And Simulation Layer For The Management Of Complex Systems

Marina Zapater Sancho, José Luis Risco Martin, Kevin Henares Vilaboa

Modeling and Simulation (M&S) is one of the most multifaceted topics present today in both industry and academia. However, we are involved in a new M&S paradigm. Systems are becoming more complex and new simulation needs arise and have to be studied. As a ...

IEEE2019

Exploiting structure of chance constrained programs via submodularity

Maryam Kamgarpour, Tony Alan Wood

We introduce a novel approach to reduce the computational effort of solving convex chance constrained programs through the scenario approach. Instead of reducing the number of required scenarios, we directly minimize the computational cost of the scenario ...

2019

MATHICSE Technical Report: Constraint-Aware Neural Networks for Riemann Problems

Jan Sickmann Hesthaven, Deep Ray

Neural networks are increasingly used in complex (data-driven) simulations as surrogates or for accelerating the computation of classical surrogates. In many applications physical constraints, such as mass or energy conservation, must be satised to obtain ...

MATHICSE2019

Fast RTO Applied to a Commercial SOFC System

Dominique Bonvin, Zacharie Wuillemin, Alejandro Gabriel Marchetti

The experimental implementation of real-time optimization (RTO) to a commercial solid-oxide fuel-cell (SOFC) system is reported in this paper. The goal of RTO is to maximize the system efficiency at steady state subject to several operating constraints. Th ...

ELSEVIER SCIENCE BV2019

Joint Learning of Semantic Alignment and Object Landmark Detection

Seungryong Kim

Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...

IEEE2019

Real-Time Optimization of Solid Oxide Fuel Cell Systems

Tafarel de Avila Ferreira

Optimization of industrial processes aims at minimizing operating cost or maximizing economic profit while respecting plant constraints. In process industry, real-time optimization (RTO) is often considered to ensure optimal plant operation and constraint ...

EPFL2019

Redshift-weighted constraints on primordial non-Gaussianity from the clustering of the eBOSS DR14 quasars in Fourier space

Cheng Zhao

We present constraints on local primordial non-Gaussianity (PNG), parametrized through f(NL)(loc), using the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. We measure and analyze the anisotropic ...

IOP PUBLISHING LTD2019

Analysis of output modifier adaptation for real-time optimization

Dominique Bonvin, Alejandro Gabriel Marchetti

In the context of real-time optimization, modifier-adaptation schemes update the model-based optimization problem by adding first-order correction terms to the cost and constraint functions of the optimization problem. This guarantees meeting the plant fir ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Nested Convex Bodies are Chaseable

Marek Elias

In the Convex Body Chasing problem, we are given an initial point v0. Rd and an online sequence of n convex bodies F1,..., Fn. When we receive Ft, we are required to move inside Ft. Our goal is to minimize the total distance traveled. This fundamental onli ...

SPRINGER2019

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